| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ArgMinMaxLayer.hpp" |
| #include "LayerCloneBase.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| |
| #include <armnnUtils/TensorUtils.hpp> |
| |
| #include <backendsCommon/WorkloadData.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| |
| namespace armnn |
| { |
| |
| ArgMinMaxLayer::ArgMinMaxLayer(const ArgMinMaxDescriptor& param, const char* name) |
| : LayerWithParameters(1, 1, LayerType::ArgMinMax, param, name) |
| { |
| } |
| |
| std::unique_ptr<IWorkload> ArgMinMaxLayer::CreateWorkload(const IWorkloadFactory& factory) const |
| { |
| ArgMinMaxQueueDescriptor descriptor; |
| return factory.CreateArgMinMax(descriptor, PrepInfoAndDesc(descriptor)); |
| } |
| |
| ArgMinMaxLayer* ArgMinMaxLayer::Clone(Graph& graph) const |
| { |
| return CloneBase<ArgMinMaxLayer>(graph, m_Param, GetName()); |
| } |
| |
| std::vector<TensorShape> ArgMinMaxLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const |
| { |
| ARMNN_ASSERT(inputShapes.size() == 1); |
| |
| TensorShape inputShape = inputShapes[0]; |
| auto inputNumDimensions = inputShape.GetNumDimensions(); |
| |
| auto axis = m_Param.m_Axis; |
| auto unsignedAxis = armnnUtils::GetUnsignedAxis(inputNumDimensions, axis); |
| |
| ARMNN_ASSERT(unsignedAxis <= inputNumDimensions); |
| |
| // 1D input shape results in scalar output |
| if (inputShape.GetNumDimensions() == 1) |
| { |
| std::vector<unsigned int> tensorDimensions(1, 1); |
| TensorShape outputShape(1, tensorDimensions.data()); |
| |
| return std::vector<TensorShape>({ outputShape }); |
| } |
| |
| std::vector<unsigned int> tensorDimensions(inputNumDimensions - 1, 0); |
| for (unsigned int i = 0; i < unsignedAxis; ++i) |
| { |
| tensorDimensions[i] = inputShape[i]; |
| } |
| |
| for (unsigned int i = unsignedAxis + 1; i < inputNumDimensions; ++i) |
| { |
| tensorDimensions[i - 1] = inputShape[i]; |
| } |
| |
| TensorShape outputShape = TensorShape(inputNumDimensions - 1, tensorDimensions.data()); |
| |
| return std::vector<TensorShape>({ outputShape }); |
| } |
| |
| void ArgMinMaxLayer::ValidateTensorShapesFromInputs() |
| { |
| VerifyLayerConnections(1, CHECK_LOCATION()); |
| |
| const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape(); |
| |
| VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); |
| |
| auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() }); |
| |
| ARMNN_ASSERT(inferredShapes.size() == 1); |
| |
| ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ArgMinMaxLayer"); |
| } |
| |
| void ArgMinMaxLayer::Accept(ILayerVisitor& visitor) const |
| { |
| visitor.VisitArgMinMaxLayer(this, GetParameters(), GetName()); |
| } |
| |
| } // namespace armnn |